Limited Resequencing for Mixed Models with Multiple Objectives
Patrick R. McMullen
DOI: 10.4236/ajor.2011.14025   PDF    HTML     5,625 Downloads   8,506 Views   Citations


This research presents a problem relevant to production scheduling for mixed models – production schedules that contain several unique items, but each unique item may have multiple units that require processing. The presented research details a variant of this problem where, over multiple processes, resequencing is permitted to a small degree so as to exploit efficiencies with the intent of optimizing the objectives of required set-ups and parts usage rate via an efficient frontier. The problem is combinatorial in nature. Enumeration is used on a variety of test problems from the literature, and a search heuristic is used to compare optimal solutions with heuristic based solutions. Experimentation shows that the heuristic solutions approach optimality, but with opportunities for improvement.

Share and Cite:

P. McMullen, "Limited Resequencing for Mixed Models with Multiple Objectives," American Journal of Operations Research, Vol. 1 No. 4, 2011, pp. 220-228. doi: 10.4236/ajor.2011.14025.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] J. Miltenburg, “Level Schedules for Mixed-Model Assembly Lines in Just in Time Production Systems,” Management Science, Vol. 35, No. 2, 1989, pp. 192-207. doi:10.1287/mnsc.35.2.192
[2] P. R. McMullen, “JIT Sequencing for Mixed-Model Assembly Lines Using Tabu Search,” Production Planning and Control, Vol. 9, No. 5, 1998, pp. 504-510. doi:10.1080/095372898233984
[3] P. R. McMullen and G. V. Frazier, “A Simulated Annealing Approach to Mixed-Model Sequencing with Multiple Objectives on a Just in Time Line,” IIE Transactions, Vol. 32, No. 8, 2000, pp. 679-686. doi:10.1080/07408170008967426
[4] A. Joly and Y. Frein, “Heuristics for an Industrial Car Sequencing Problem Considering Paint and Assembly Shope Objectives,” Computers & Industrial Engineering, Vol. 55, No. 2, 2008, pp. 295-310. doi:10.1016/j.cie.2007.12.014
[5] M. Masin and Y. Bukchin, “Diversity Maximization Approach for Multiobjective Optimization,” Operations Research, Vol. 56, No. 2, 2008, pp. 411-424. doi:10.1287/opre.1070.0413
[6] M. Lahmar and S. Banjaafar, “Sequencing with Limited Flexibility,” IIE Transactions, Vol. 39, No. 10, 2007, pp. 937-955. doi:10.1080/07408170701416665
[7] P. R. McMullen, “A Kohonen Self-Organizing Map Approach to Addressing a Multiple Objective, Mixed Model JIT Sequencing Problem,” International Journal of Production Economics, Vol. 72, No. 1, 2001, pp. 59-71. doi:10.1016/S0925-5273(00)00091-8
[8] LINGO, “The Modeling Language and Optimizer,” LINDO Systems, Inc., Chicago, 1995.
[9] S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi, “Optimization by Simulated Annealing,” Science, Vol. 220, No. 4598, 1983, pp. 671-679. doi:10.1126/science.220.4598.671
[10] R. W. Eglese, “Simulated Annealing: A Tool for Operational Research,” European Journal of Operational Research, Vol. 46, No. 3, 1990, pp. 271-281. doi:10.1016/0377-2217(90)90001-R
[11] J. H. Holland, “Adaptation in Natural and Artificial Systems,” University of Michigan Press, Ann Arbor, 1975.
[12] F. Glover, “Tabu Search: A Tutorial,” Interfaces, Vol. 20, No. 1, 1990, pp. 74-94. doi:10.1287/inte.20.4.74
[13] M. Dorigo and L. M. Gambardella, “Ant Colonies for the Traveling Salesman Problem,” Biosystem, Vol. 43, No. 1, 1997, pp. 73-81. doi:10.1016/S0303-2647(97)01708-5
[14] N. Metropolis, A. Rosenbluth, N. Rosenbluth, A. Teller and E. Teller, “Equation of State Calculations by Fast Computing Machines,” Journal of Chemical Physics, Vol. 51, No. 6, 1953, pp. 177-190.
[15] P. R. McMullen, “An Ant Colony Optimization Approach to Addressing a JIT Sequencing Problem with Multiple Objective,” Artificial Intelligence in Engineering, Vol. 15, No. 3, 2001, pp. 309-317. doi:10.1016/S0954-1810(01)00004-8
[16] R. Sedgewick, “Algorithms in Java,” 3rd Edition, Addison-Wesley, New York.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.